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ch05/01_main-chapter-code/ch05.ipynb
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@@ -471,7 +471,7 @@
"metadata": {},
"source": [
"- We want to maximize all these values, bringing them close to a probability of 1\n",
"- In mathematical optimization, it is easier to maximize the logarithm of the probability score than the probability score itself; this is out of the scope of this book, but I have recorded a lecture with more details here: L8.2 Logistic Regression Loss Function, [https://www.youtube.com/watch?v=GxJe0DZvydM](https://www.youtube.com/watch?v=GxJe0DZvydM)"
"- In mathematical optimization, it is easier to maximize the logarithm of the probability score than the probability score itself; this is out of the scope of this book, but I have recorded a lecture with more details here: [L8.2 Logistic Regression Loss Function](https://www.youtube.com/watch?v=GxJe0DZvydM)"
]
},
{
@@ -2439,7 +2439,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.4"
"version": "3.10.12"
}
},
"nbformat": 4,